# model
model_name = 'RWKV'
use_checkpoint = None
feature_size = 4096
hidden_size = 256
max_frames = 25
nbits = 64
S5VH_type = 'small'

# dataset
dataset = 'ucf'
workers = 12
batch_size = 128
mask_ratio = 0.5

# train
seed = 1
num_epochs = 350
alpha = 1.0
temperature = 0.5
tau_plus = 0.1
train_num_sample = 9537

# Reliability-Aware Hash Center Alignment
a_cluster = 0.1
temperature_cluster = 0.5
nclusters  = 100
warm_epoch = 50
smoothing_alpha = 0.01

# test
test_batch_size = 128
test_num_sample = 9537 
query_num_sample = 3783 

# optimizer
optimizer_name = 'AdamW'
schedule ="CosineAnnealingLR" #'StepLR'
lr = 5e-4
min_lr = 1e-5

# path
data_root = '/data2/lianniu/dataset/ucf4/'
home_root = '/data2/lianniu/'

# path:train
train_feat_path = [data_root + 'ucf_train_feats.h5']
train_assist_path = data_root+'final_train_train_assit.h5' 
latent_feat_path = data_root+'final_train_latent_feats.h5'
anchor_path = data_root+'final_train_anchors.h5'
sim_path = data_root+'final_train_sim_matrix.h5'

# path:test
test_feat_path = [data_root + 'ucf_train_feats.h5'] # database
label_path = [data_root + 'ucf_train_labels.mat']
query_feat_path = [data_root + 'ucf_test_feats.h5'] # query
query_label_path = [data_root + 'ucf_test_labels.mat']

# path:save
save_dir = home_root + 'saved_model/' + dataset + "/" + model_name
file_path = save_dir + '_' + str(nbits) + 'bit'
